USE CASE: High-Precision Visualization of Wildlife Dynamics & Habitat Movement

Dynamic Simulation of Wildlife Damage Risks and Automated Mitigation Proposal via AI × GIS

Background

In semi-mountainous and rural regions, damage to crops and intrusion into living environments caused by wild animals (such as wild boars, monkeys, and deer) have become severe social issues. Traditionally, trap placement and protective fence installation relied heavily on field intuition and experience. This created major hurdles, including uncertain effectiveness, heavy workloads for regular inspection, and difficulties in reaching consensus among stakeholders (local governments, hunting associations, and local residents).

To verify highly effective, data-driven mitigation approaches, we conducted modeling using simulated wildlife sighting and capture data, along with detailed topographical and environmental data from Kuwana City, Mie Prefecture. By utilizing a geospatial analysis engine, we achieved real-time mitigation simulation and automated AI proposals.

Key Features of the UI & Analysis System

This system provides an intuitive interface to simulate the entire workflow—from visualizing potential habitat risks to estimating movement routes based on environmental factors, and calculating optimal mitigation measures with automated proposal generation.

• Habitat Suitability Modeling via Geospatial Data

  Integrates sighting and capture data with diverse environmental factors such as terrain and vegetation. It visualizes the settlement and concealment risks (habitat potential) of target species across the region as a continuous spatial distribution map.

• Movement Path Simulation Reflecting Animal Behavior

  Simulates the behavioral traits of animals navigating cover areas while avoiding obstacles and human activity zones. By factoring in resistance (travel cost) from topography and physical barriers, it accurately estimates highly utilized animal trails and intrusion routes.

• Dynamic Simulation & Automated AI Proposals Based on Custom Criteria

  Allows users to flexibly adjust priorities on the Web UI for parameters such as "Movement Routes," "Habitat Risk," "Inspection Accessibility," and "Safety/Legal Regulations." The system calculates optimal mitigation points and protective routes based on these conditions, while advanced AI instantly generates practical, localized mitigation proposals tailored to regional characteristics.

Key Insights & Application Scenarios

The dynamic forecasting model and simulation environment provided by this technology support decision-making and efficient field operations for local governments and regional wildlife management teams:

• Optimal Placement Planning for Traps & Protective Fences

  Identifies bottlenecks (concentrated transit points) and high-risk zones in advance, guiding trap placement for high capture efficiency and protective fence plans with maximum shielding effect.

• Pre-estimation of Inspection Workload & Maintenance Costs

  Incorporates field accessibility and safety regulations into simulations upfront, reducing post-installation routine inspection and maintenance burdens while supporting optimal budget allocation.

• Rapid Evidence-Based Stakeholder Consensus

  Uses objective spatial maps—moving away from reliance on intuition—and AI-generated rationale to align perspectives among municipal officials, hunting associations, and local residents, facilitating smooth decision-making.

Expansion & Future Rollout of This Use Case

This simulation framework can be flexibly and rapidly deployed across diverse regions and ecological contexts simply by swapping species behavioral parameters and regional GIS data. Building upon the deployment model established using simulated data, we are expanding this solution nationwide to municipalities and regions struggling with wildlife damage. Furthermore, supported by a secure data management structure, it ensures safe deployment and operation even when handling highly sensitive regional information.